
#pragma nodebook off
#Use nodebook for better reproducibility https://github.com/uoa-eResearch/nodebook
%reload_ext nodebook.ipython
%nodebook disk phase3


# load libraries
import geopandas as gpd # vector data
import pandas as pd # tabular data, loading CSVs
import numpy as np # numeric data
from util import *
import matplotlib # plotting
import contextily as ctx # Used for contextual basemaps
from matplotlib_scalebar.scalebar import ScaleBar # scalebar for plot
import matplotlib.pyplot as plt # plotting
from tqdm.auto import tqdm # progress bars
tqdm.pandas()
import json
from shapely.geometry import Point, shape, LineString, MultiLineString, GeometryCollection, MultiPoint, Polygon  # creating points
import requests # web requests
from pandarallel import pandarallel # parallel operations for speed
pandarallel.initialize(progress_bar=True)
plt.rcParams['figure.figsize'] = (20, 20)

INFO: Pandarallel will run on 16 workers.
INFO: Pandarallel will use Memory file system to transfer data between the main process and workers.


ls()

Total: 1300.0MB


ls("restricted")

Total: 223.0MB


df = pd.read_csv("restricted/QPIDs_Auckland_1990_2020.csv")
df = gpd.GeoDataFrame(df, geometry=gpd.points_from_xy(df.CL_Longitude, df.CL_Latitude), crs="EPSG:4326")
df = df.set_index("CL_QPID_output2")
df


%%time
parcels = gpd.read_file('input/lds-nz-primary-parcels-FGDB.zip!nz-primary-parcels.gdb')
parcels = parcels.to_crs(df.crs)
parcels = parcels.set_index("id")
parcels["parcel_geometry"] = parcels.geometry

CPU times: user 39.2 s, sys: 1.45 s, total: 40.7 s
Wall time: 41.4 s


parcels


%%time
df = gpd.sjoin(df, parcels, how="left")

CPU times: user 38.9 s, sys: 2.21 s, total: 41.1 s
Wall time: 41.3 s


df.parcel_intent.value_counts()

DCDB                                                                 276092
Fee Simple Title                                                      99917
Legalisation                                                             79
Road                                                                      3
Vesting on Deposit for Local Purpose Reserve                              2
Vesting on Deposit for Recreation Reserve (Territorial Authority)         1
Name: parcel_intent, dtype: int64


# Roads shouldn't be in this dataset - might have to give these 3 points a little nudge


sold_roads = df[df.parcel_intent == "Road"]
for i in range(len(sold_roads)):
    sold_road = sold_roads.iloc[i:i+1]
    display(sold_road)
    ax = sold_road.parcel_geometry.to_crs(epsg=3857).plot(alpha=.5)
    sold_road.parcel_geometry.centroid.to_crs(epsg=3857).plot(ax=ax, color="red")
    sold_road.to_crs(epsg=3857).plot(ax=ax, color="green")
    ctx.add_basemap(ax, source=ctx.providers.Esri.WorldImagery, zoom=21 if i == 0 else "auto")
    ax.set_title("Red = parcel centroid, green = QPID latlong")
    plt.show()

<string>:6: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.

<string>:6: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.

<string>:6: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.


df.at[258637, "parcel_intent"] = "Glitch?"


print(f"{1e-4} degrees equates to {df.loc[[1528194]].to_crs(epsg=2193).distance(df.loc[[1528194]].translate(yoff=-1e-4).to_crs(epsg=2193)).iloc[0]} meters")

0.0001 degrees equates to 11.09551261419352 meters


problems = [1528194, 1779952]
display(df.loc[problems])
# Nudge point south a little bit
df.geometry[1528194] = df.loc[[1528194]].translate(yoff=-1e-4)
# Nudge point west a little bit
df.geometry[1779952] = df.loc[[1779952]].translate(xoff=-1e-4)

# Redo the join for these newly adjusted points
subset = df.loc[df.index.isin(problems), ["CL_Longitude", "CL_Latitude", "QPID_vintage", "geometry"]]
df.loc[problems] = gpd.sjoin(subset, parcels)
display(df.loc[problems])


df.parcel_intent.value_counts()

DCDB                                                                 276094
Fee Simple Title                                                      99917
Legalisation                                                             79
Vesting on Deposit for Local Purpose Reserve                              2
Glitch?                                                                   1
Vesting on Deposit for Recreation Reserve (Territorial Authority)         1
Name: parcel_intent, dtype: int64


df = df.rename(columns={"titles": "LINZ_parcel_ID"})
df.index_right = df.index_right.astype('Int64')
df


sum(pd.isna(df.LINZ_parcel_ID))

7202


df.LINZ_parcel_ID.sample(10)

CL_QPID_output2
1656620                                 NA112B/92, NA92A/927
2778909                                               553672
2982737                                               708817
311957                                             NA33C/665
151569                                  NA43B/133, NA43B/134
269750                                                  None
1585992                                            NA69D/640
162868                                             NA1B/1263
1576972                                            NA20A/590
2326202    121037, 123163, 126156, 126160, 126161, 126162...
Name: LINZ_parcel_ID, dtype: object


df["LINZ_parcel_centroid_lon"] = df.parcel_geometry.centroid.x
df["LINZ_parcel_centroid_lat"] = df.parcel_geometry.centroid.y

<string>:1: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.

<string>:2: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.


sample_parcels = parcels.cx[174.782:174.783, -36.870:-36.871]


ax = sample_parcels.to_crs(epsg=3857).plot(column="parcel_intent", legend=True, alpha=.5, categorical=True, edgecolor="black")
sample_parcels.centroid.to_crs(epsg=3857).plot(ax=ax, color="red")
df[df.index_right.isin(sample_parcels.index)].to_crs(epsg=3857).plot(ax=ax, color="green")
ctx.add_basemap(ax, source=ctx.providers.Esri.WorldImagery)
plt.title("Red = parcel centroid, green = QPID latlong")

<string>:2: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.

Text(0.5, 1.0, 'Red = parcel centroid, green = QPID latlong')


pd.Series(type(a) for a in df.parcel_geometry).value_counts()

<class 'shapely.geometry.multipolygon.MultiPolygon'>    376094
<class 'NoneType'>                                        7178
dtype: int64


%%time
def extract_verts(geometry):
    lat = np.nan
    lng = np.nan
    if geometry:
        coordinates = []
        for polygon in geometry:
            coordinates.extend(polygon.exterior.coords)
        lng = f"[{'; '.join([str(round(point[0], 6)) for point in coordinates])}]"
        lat = f"[{'; '.join([str(round(point[1], 6)) for point in coordinates])}]"
    return pd.Series([lng, lat])
df[["LINZ_parcel_vertices_lon", "LINZ_parcel_vertices_lat"]] = df.parcel_geometry.progress_apply(extract_verts)

<string>:6: ShapelyDeprecationWarning: Iteration over multi-part geometries is deprecated and will be removed in Shapely 2.0. Use the `geoms` property to access the constituent parts of a multi-part geometry.

CPU times: user 1min 27s, sys: 2.29 s, total: 1min 29s
Wall time: 1min 27s


sample = df.iloc[0]
sample

/usr/local/lib/python3.8/dist-packages/pandas/core/dtypes/inference.py:383: ShapelyDeprecationWarning: Iteration over multi-part geometries is deprecated and will be removed in Shapely 2.0. Use the `geoms` property to access the constituent parts of a multi-part geometry.
  iter(obj)  # Can iterate over it.
/usr/local/lib/python3.8/dist-packages/pandas/core/dtypes/inference.py:384: ShapelyDeprecationWarning: __len__ for multi-part geometries is deprecated and will be removed in Shapely 2.0. Check the length of the `geoms` property instead to get the  number of parts of a multi-part geometry.
  len(obj)  # Has a length associated with it.
/usr/local/lib/python3.8/dist-packages/pandas/io/formats/printing.py:118: ShapelyDeprecationWarning: Iteration over multi-part geometries is deprecated and will be removed in Shapely 2.0. Use the `geoms` property to access the constituent parts of a multi-part geometry.
  s = iter(seq)
/usr/local/lib/python3.8/dist-packages/pandas/io/formats/printing.py:122: ShapelyDeprecationWarning: __len__ for multi-part geometries is deprecated and will be removed in Shapely 2.0. Check the length of the `geoms` property instead to get the  number of parts of a multi-part geometry.
  for i in range(min(nitems, len(seq)))
/usr/local/lib/python3.8/dist-packages/pandas/io/formats/printing.py:126: ShapelyDeprecationWarning: __len__ for multi-part geometries is deprecated and will be removed in Shapely 2.0. Check the length of the `geoms` property instead to get the  number of parts of a multi-part geometry.
  if nitems < len(seq):

CL_Longitude                                                       174.588941
CL_Latitude                                                        -36.186076
QPID_vintage                                                             2020
geometry                           POINT (174.588940530675 -36.1860763144825)
index_right                                                           5128312
appellation                                        Part Allot S25 PSH OF Arai
affected_surveys                                                         None
parcel_intent                                                            DCDB
topology_type                                                         Primary
statutory_actions                                                        None
land_district                                                  North Auckland
LINZ_parcel_ID                                                       NA589/73
survey_area                                                               NaN
calc_area                                                              2913.0
parcel_geometry             (POLYGON ((174.5887711830001 -36.1863244329999...
LINZ_parcel_centroid_lon                                           174.589185
LINZ_parcel_centroid_lat                                           -36.186039
LINZ_parcel_vertices_lon    [174.588771; 174.588883; 174.589331; 174.58955...
LINZ_parcel_vertices_lat    [-36.186324; -36.185872; -36.18579; -36.186183...
Name: 75494, dtype: object


%%time
xmin, ymin, xmax, ymax = sample.parcel_geometry.bounds
search_area = parcels.cx[xmin:xmax, ymin:ymax]
neighbours = search_area[search_area.touches(sample.parcel_geometry)]
neighbours

CPU times: user 12.2 s, sys: 501 ms, total: 12.7 s
Wall time: 12.8 s


search_area.parcel_intent[sample.index_right] = "AOI"
cmap = matplotlib.colors.ListedColormap(['red', 'blue', 'green', 'pink'])
ax = search_area.to_crs(epsg=3857).plot(column="parcel_intent", cmap=cmap, legend=True, categorical=True, alpha=.5)
roads = neighbours[neighbours.parcel_intent == "Road"]
intersection = roads.geometry.intersection(sample.parcel_geometry)
intersection.to_crs(epsg=3857).plot(ax=ax, color="red", linewidth=5)
ctx.add_basemap(ax, url=ctx.providers.Esri.WorldImagery)

<string>:1: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
<string>:7: FutureWarning: The "url" option is deprecated. Please use the "source" argument instead.


%%time
roads = parcels[parcels.parcel_intent == "Road"]

CPU times: user 11.9 s, sys: 470 ms, total: 12.4 s
Wall time: 12.6 s


%%time
def extract_road_intersections(geom):
    if geom:
        xmin, ymin, xmax, ymax = geom.bounds
        neighbouring_roads = roads.cx[xmin:xmax, ymin:ymax]
        return neighbouring_roads.geometry.intersection(geom).unary_union
    return np.nan
road_intersections = df.parcel_geometry.parallel_apply(extract_road_intersections)

CPU times: user 11min 8s, sys: 31.7 s, total: 11min 40s
Wall time: 1h 23min 27s


types = pd.Series(type(i) for i in road_intersections)
types.index = road_intersections.index
types.value_counts()

<class 'shapely.geometry.linestring.LineString'>              199991
<class 'shapely.geometry.multilinestring.MultiLineString'>    141418
<class 'NoneType'>                                             40163
<class 'shapely.geometry.collection.GeometryCollection'>        1290
<class 'shapely.geometry.point.Point'>                           393
<class 'shapely.geometry.multipoint.MultiPoint'>                  16
<class 'shapely.geometry.polygon.Polygon'>                         1
dtype: int64


display(df[types == Polygon])


geom = df.parcel_geometry[258637]
xmin, ymin, xmax, ymax = geom.bounds
neighbouring_roads = roads.cx[xmin:xmax, ymin:ymax]
neighbouring_roads = neighbouring_roads[neighbouring_roads.touches(geom)]
road_intersections[258637] = neighbouring_roads.geometry.intersection(geom).unary_union
types[258637] = type(road_intersections[258637])


types.value_counts()

<class 'shapely.geometry.linestring.LineString'>              199991
<class 'shapely.geometry.multilinestring.MultiLineString'>    141419
<class 'NoneType'>                                             40163
<class 'shapely.geometry.collection.GeometryCollection'>        1290
<class 'shapely.geometry.point.Point'>                           393
<class 'shapely.geometry.multipoint.MultiPoint'>                  16
dtype: int64


collections = road_intersections[types == GeometryCollection]


collection_types = []
for c in collections:
    collection_types.extend(type(o) for o in c)
pd.Series(collection_types).value_counts()

<string>:3: ShapelyDeprecationWarning: Iteration over multi-part geometries is deprecated and will be removed in Shapely 2.0. Use the `geoms` property to access the constituent parts of a multi-part geometry.

<class 'shapely.geometry.linestring.LineString'>    1245
<class 'shapely.geometry.point.Point'>               572
<class 'shapely.geometry.polygon.Polygon'>             2
dtype: int64


for i, c in collections.iteritems():
    if Polygon in [type(o) for o in c]:
        print(i)

2211389
2232849

<string>:2: ShapelyDeprecationWarning: Iteration over multi-part geometries is deprecated and will be removed in Shapely 2.0. Use the `geoms` property to access the constituent parts of a multi-part geometry.


problems = df.loc[[2211389, 2232849]]
display(problems)

xmin, ymin, xmax, ymax = problems.parcel_geometry.unary_union.bounds
search_area = parcels.cx[xmin:xmax, ymin:ymax]

search_area.parcel_intent[problems.index_right] = "AOI"
cmap = matplotlib.colors.ListedColormap(['red', 'blue', 'green', 'pink'])
ax = search_area.to_crs(epsg=3857).plot(column="parcel_intent", cmap=cmap, legend=True, categorical=True, alpha=.5, edgecolor="black")
roads = search_area[search_area.parcel_intent == "Road"]
intersection = roads.geometry.intersection(problems.parcel_geometry.unary_union)
intersection.to_crs(epsg=3857).plot(ax=ax, color="red", linewidth=5)
intersection.boundary.to_crs(epsg=3857).plot(ax=ax, color="blue", linewidth=5)
display(intersection)
ctx.add_basemap(ax, source=ctx.providers.Esri.WorldImagery)

<string>:7: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
/usr/local/lib/python3.8/dist-packages/pandas/core/series.py:1135: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  self._set_values(indexer, value)

id
6616875    POLYGON ((174.69072 -36.76480, 174.69053 -36.7...
6606001    MULTILINESTRING ((174.69112 -36.76474, 174.691...
6616867    MULTILINESTRING ((174.69053 -36.76494, 174.690...
6606004    POLYGON ((174.69072 -36.76480, 174.69072 -36.7...
dtype: geometry


%%time
LINZ_parcel_roadvertices_lon = []
LINZ_parcel_roadvertices_lat = []
for intersection in tqdm(road_intersections):
    lat = np.nan
    lon = np.nan
    if intersection:
        lat = set()
        lon = set()
        try:
            if type(intersection) in (LineString, Point):
                lon.update(intersection.xy[0])
                lat.update(intersection.xy[1])
            elif type(intersection) in (MultiLineString, GeometryCollection, MultiPoint):
                for p in intersection.geoms:
                    if type(p) == Polygon:
                        lon.update(p.exterior.xy[0])
                        lat.update(p.exterior.xy[1])
                    else:
                        lon.update(p.xy[0])
                        lat.update(p.xy[1])
            else:
                raise Exception(f"Don't know how to handle {type(intersection)}")
        except:
            print(type(intersection))
            print(intersection)
            raise
        lon = f"[{'; '.join([str(round(lon, 6)) for lon in list(lon)])}]"
        lat = f"[{'; '.join([str(round(lat, 6)) for lat in list(lat)])}]"
    LINZ_parcel_roadvertices_lon.append(lon)
    LINZ_parcel_roadvertices_lat.append(lat)
df["LINZ_parcel_roadvertices_lon"] = LINZ_parcel_roadvertices_lon
df["LINZ_parcel_roadvertices_lat"] = LINZ_parcel_roadvertices_lat

CPU times: user 39.8 s, sys: 776 ms, total: 40.6 s
Wall time: 40.5 s

df


df.drop(columns="parcel_geometry").to_csv("restricted/QPIDs_Auckland_1990_2020_augmented.csv")

	name	filesize (MB)	last modified
0	2013-mb-dataset-Total-New-Zealand-Household.csv	37.12	2014-06-04 10:56:30.000000
1	2013-mb-dataset-Total-New-Zealand-Individual-Part-1.csv	31.66	2014-04-01 10:13:15.197000
2	2013_census_mean_income_by_AU2013.xlsx	0.59	2021-09-07 06:21:24.000000
3	2018-census-electoral-population-meshblock-2020-data.csv	5.60	2021-08-09 00:39:18.000000
4	2018_census_dwellings_by_SA2.xlsx	0.43	2021-07-12 14:30:28.000000
5	AC_Special_Housing_Area.zip	0.29	2021-09-02 10:36:16.760000
6	AucklandArea.gpkg	0.09	2021-09-02 10:36:17.220000
7	Geocoordinates_Direct_Transit_stops_AKL.xlsx	0.01	2020-10-08 07:52:29.000000
8	Individual_part1_totalNZ-wide_format_updated_16-7-20.csv	36.58	2020-07-14 16:12:24.000000
9	MASTER_UP_BaseZone_SHP.zip	66.92	2021-07-19 02:23:51.137347
10	Modified_Community_Boards_SHP.zip	1.30	2021-07-19 02:16:07.650000
11	area-unit-2013.gdb.zip	14.21	2021-09-02 10:36:16.070000
12	kx-nz-state-highway-on-ramps-off-ramps-SHP.zip	0.14	2021-08-25 09:52:06.341291
13	lds-nz-coastline-mean-high-water-FGDB.zip	4.88	2021-08-31 16:25:16.250000
14	lds-nz-coastlines-and-islands-polygons-topo-150k-FGDB.zip	4.25	2021-08-05 15:57:49.020000
15	lds-nz-primary-parcels-CLIPPED-4326.gpkg	273.35	2021-09-02 10:37:32.410000
16	lds-nz-primary-parcels-FGDB.zip	79.03	2021-08-12 09:13:27.910000
17	lds-nz-railway-centrelines-topo-150k-SHP.zip	0.87	2021-08-31 10:01:46.315326
18	lds-nz-road-centrelines-topo-150k-FGDB.zip	36.06	2021-08-31 09:43:07.931704
19	lds-nz-street-address-GPKG-CLIPPED.gpkg	170.23	2021-09-02 10:37:19.490000
20	lds-nz-street-address-GPKG.zip	200.88	2021-09-02 10:37:26.070000
21	meshblock-2013.gdb.zip	106.57	2021-09-02 10:36:59.860000
22	meshblock-2018-clipped-generalised.gdb.zip	32.83	2021-09-02 10:36:26.010000
23	nz-primary-parcels.gdb.zip	55.00	2021-09-02 10:36:39.020000
24	statsnzarea-unit-2013-FGDB.zip	13.79	2021-08-31 16:56:17.150000
25	statsnzmeshblock-higher-geographies-2018-generalised-FGDB.zip	34.54	2021-08-05 14:53:54.350000
26	statsnzpopulation-by-meshblock-2013-census-FGDB.zip	82.11	2021-07-19 13:53:55.150631
27	statsnzstatistical-area-2-higher-geographies-2018-clipped-generalis-FGDB.zip	10.72	2021-08-30 17:12:55.591895

	name	filesize (MB)	last modified
0	QPIDs_Auckland_1990_2020.csv	17.40	2021-07-07 13:09:39.000
1	QPIDs_Auckland_1990_2020_augmented.csv	205.58	2021-09-07 12:36:15.880

	CL_Longitude	CL_Latitude	QPID_vintage	geometry
CL_QPID_output2
75494	174.588941	-36.186076	2020	POINT (174.58894 -36.18608)
75499	174.581811	-36.200345	2020	POINT (174.58181 -36.20034)
75639	174.496590	-36.228740	2020	POINT (174.49659 -36.22874)
75640	174.498361	-36.228827	2020	POINT (174.49836 -36.22883)
75654	174.493736	-36.229990	2020	POINT (174.49374 -36.22999)
...	...	...	...	...
3160123	174.728112	-36.408104	2018	POINT (174.72811 -36.40810)
3160124	174.728164	-36.408113	2018	POINT (174.72816 -36.40811)
3160630	174.655992	-36.509925	2018	POINT (174.65599 -36.50992)
3164546	174.537978	-36.774834	2018	POINT (174.53798 -36.77483)
3166852	174.644137	-36.854796	2018	POINT (174.64414 -36.85480)

	appellation	affected_surveys	parcel_intent	topology_type	statutory_actions	land_district	titles	survey_area	calc_area	geometry	parcel_geometry
id
5266447	None	None	Hydro	Primary	None	North Auckland	None	NaN	1289690.0	MULTIPOLYGON (((174.46092 -36.26249, 174.46083...	MULTIPOLYGON (((174.46092 -36.26249, 174.46083...
4789727	Part Lot 3 Allot 64 Section 1 SBRS OF Auckland	SO 663	DCDB	Primary	None	North Auckland	None	NaN	1.0	MULTIPOLYGON (((174.77836 -36.85187, 174.77838...	MULTIPOLYGON (((174.77836 -36.85187, 174.77838...
4810316	Part Tidal Lands of Manukau Harbour Survey Off...	SO 67474	DCDB	Primary	[Create] Revested in the Crown Sec 5 Foreshore...	North Auckland	None	31600000.0	31342451.0	MULTIPOLYGON (((174.68836 -37.01631, 174.68898...	MULTIPOLYGON (((174.68836 -37.01631, 174.68898...
4817943	Crown Land Survey Office Plan 58175	SO 58175	DCDB	Primary	[Create] Crown Land Reserved from Sale Sec 58 ...	North Auckland	None	NaN	467490.0	MULTIPOLYGON (((174.33091 -36.32797, 174.33059...	MULTIPOLYGON (((174.33091 -36.32797, 174.33059...
4827816	Lot 2 DP 165098	DP 165098	DCDB	Primary	None	North Auckland	NA99B/977	22979.0	22972.0	MULTIPOLYGON (((174.73406 -36.69245, 174.73408...	MULTIPOLYGON (((174.73406 -36.69245, 174.73408...
...	...	...	...	...	...	...	...	...	...	...	...
7291940	Lot 745 DP 433546	DP 433546	Fee Simple Title	Primary	None	North Auckland	528968	247.0	247.0	MULTIPOLYGON (((174.93787 -37.03903, 174.93763...	MULTIPOLYGON (((174.93787 -37.03903, 174.93763...
7266269	Lot 533 DP 427884	DP 427884, LT 454543	Fee Simple Title	Primary	None	North Auckland	520875	336.0	336.0	MULTIPOLYGON (((174.93990 -37.03814, 174.94015...	MULTIPOLYGON (((174.93990 -37.03814, 174.94015...
8051540	Lot 8 DP 533517	DP 533517	Fee Simple Title	Primary	None	North Auckland	876934	185.0	185.0	MULTIPOLYGON (((174.67269 -36.59236, 174.67269...	MULTIPOLYGON (((174.67269 -36.59236, 174.67269...
7264065	Lot 518 DP 429024	DP 429024	Fee Simple Title	Primary	None	North Auckland	513803	313.0	313.0	MULTIPOLYGON (((174.93753 -37.03880, 174.93747...	MULTIPOLYGON (((174.93753 -37.03880, 174.93747...
7266268	Lot 532 DP 427884	DP 427884, LT 454543	Fee Simple Title	Primary	None	North Auckland	520874	331.0	331.0	MULTIPOLYGON (((174.94009 -37.03794, 174.94015...	MULTIPOLYGON (((174.94009 -37.03794, 174.94015...

	CL_Longitude	CL_Latitude	QPID_vintage	geometry	index_right	appellation	affected_surveys	parcel_intent	topology_type	statutory_actions	land_district	LINZ_parcel_ID	survey_area	calc_area	parcel_geometry
CL_QPID_output2
75494	174.588941	-36.186076	2020	POINT (174.58894 -36.18608)	5128312	Part Allot S25 PSH OF Arai	None	DCDB	Primary	None	North Auckland	NA589/73	NaN	2913.0	MULTIPOLYGON (((174.58877 -36.18632, 174.58888...
75499	174.581811	-36.200345	2020	POINT (174.58181 -36.20034)	5128309	Lot 2 DP 130303	DP 130303	DCDB	Primary	None	North Auckland	NA76B/662	9859.0	8620.0	MULTIPOLYGON (((174.58154 -36.20156, 174.58161...
75639	174.496590	-36.228740	2020	POINT (174.49659 -36.22874)	4823770	Part Otioro & Te Topuni A2A Block	ML 9928	DCDB	Primary	None	North Auckland	NA1373/48	8296.0	7490.0	MULTIPOLYGON (((174.49514 -36.22889, 174.49701...
75640	174.498361	-36.228827	2020	POINT (174.49836 -36.22883)	4697657	Lot 1 DP 44316	DP 44316	DCDB	Primary	None	North Auckland	NA1373/47	3667.0	4152.0	MULTIPOLYGON (((174.49863 -36.22877, 174.49862...
75654	174.493736	-36.229990	2020	POINT (174.49374 -36.22999)	5202126	Lot 1 DP 52926	DP 52926	DCDB	Primary	None	North Auckland	NA8B/226	3331.0	3323.0	MULTIPOLYGON (((174.49427 -36.23026, 174.49386...
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
3160123	174.728112	-36.408104	2018	POINT (174.72811 -36.40810)	7974171	Lot 82 DP 521864	DP 521864	Fee Simple Title	Primary	None	North Auckland	826394	39.0	40.0	MULTIPOLYGON (((174.72813 -36.40815, 174.72812...
3160124	174.728164	-36.408113	2018	POINT (174.72816 -36.40811)	7974172	Lot 83 DP 521864	DP 521864	Fee Simple Title	Primary	None	North Auckland	826395	39.0	40.0	MULTIPOLYGON (((174.72813 -36.40815, 174.72814...
3160630	174.655992	-36.509925	2018	POINT (174.65599 -36.50992)	7440747	Lot 2 DP 460961	DP 460961	Fee Simple Title	Primary	None	North Auckland	605470	4500.0	4495.0	MULTIPOLYGON (((174.65635 -36.51025, 174.65624...
3164546	174.537978	-36.774834	2018	POINT (174.53798 -36.77483)	7987560	Lot 1 DP 533552	DP 533552	Fee Simple Title	Primary	None	North Auckland	878889	62163.0	62143.0	MULTIPOLYGON (((174.53978 -36.77485, 174.53974...
3166852	174.644137	-36.854796	2018	POINT (174.64414 -36.85480)	7799795	Section 36 SO 498829	SO 498829	Fee Simple Title	Primary	[Create] Fee Simple Title New Zealand Gazette ...	North Auckland	900731	1460.0	1459.0	MULTIPOLYGON (((174.64432 -36.85494, 174.64428...

Phase 3: Residential Property Transaction Dataset¶

INPUTS¶

OUTPUTS¶

	CL_Longitude	CL_Latitude	QPID_vintage	geometry	index_right	appellation	affected_surveys	parcel_intent	topology_type	statutory_actions	land_district	titles	survey_area	calc_area	parcel_geometry
CL_QPID_output2
258637	174.84187	-36.903922	2020	POINT (174.84187 -36.90392)	7515185.0	Section 1 SO 471988	SO 471988, SO 509515	Road	Primary	[Create] Land declared Road New Zealand Gazett...	North Auckland	None	690.0	688.0	MULTIPOLYGON (((174.84229 -36.90402, 174.84226...

	CL_Longitude	CL_Latitude	QPID_vintage	geometry	index_right	appellation	affected_surveys	parcel_intent	topology_type	statutory_actions	land_district	titles	survey_area	calc_area	parcel_geometry
CL_QPID_output2
1528194	174.642663	-36.59097	2020	POINT (174.64266 -36.59097)	6605265.0	None	SO 70497	Road	Primary	[Create] Road New Zealand Gazette 2002 p 4425	North Auckland	None	NaN	31611.0	MULTIPOLYGON (((174.63916 -36.58870, 174.63934...

	CL_Longitude	CL_Latitude	QPID_vintage	geometry	index_right	appellation	affected_surveys	parcel_intent	topology_type	statutory_actions	land_district	titles	survey_area	calc_area	parcel_geometry
CL_QPID_output2
1779952	174.749001	-36.823758	2020	POINT (174.74900 -36.82376)	5222196.0	None	None	Road	Primary	None	North Auckland	None	NaN	3462.0	MULTIPOLYGON (((174.74895 -36.82419, 174.74897...

	appellation	affected_surveys	parcel_intent	topology_type	statutory_actions	land_district	titles	survey_area	calc_area	geometry	parcel_geometry
id
5207551	None	None	Road	Primary	None	North Auckland	None	NaN	8063.0	MULTIPOLYGON (((174.58888 -36.18587, 174.58877...	MULTIPOLYGON (((174.58888 -36.18587, 174.58877...
5224880	None	None	Road	Primary	None	North Auckland	None	NaN	10916.0	MULTIPOLYGON (((174.58967 -36.18646, 174.58967...	MULTIPOLYGON (((174.58967 -36.18646, 174.58967...
4941664	Lot 2 DP 130126	DP 130126	DCDB	Primary	None	North Auckland	NA131B/147	21810.0	21780.0	MULTIPOLYGON (((174.59156 -36.18479, 174.59187...	MULTIPOLYGON (((174.59156 -36.18479, 174.59187...
6744495	Lot 43 DP 340819	DP 340819, DP 477278, LT 409850	Fee Simple Title	Primary	None	North Auckland	661091	1529.0	1528.0	MULTIPOLYGON (((174.58907 -36.18508, 174.58920...	MULTIPOLYGON (((174.58907 -36.18508, 174.58920...
7558496	Lot 16 DP 477278	DP 477278, LT 494228	Fee Simple Title	Primary	None	North Auckland	661091	6043.0	6041.0	MULTIPOLYGON (((174.58872 -36.18652, 174.58877...	MULTIPOLYGON (((174.58872 -36.18652, 174.58877...

	CL_Longitude	CL_Latitude	QPID_vintage	geometry	index_right	appellation	affected_surveys	parcel_intent	topology_type	statutory_actions	land_district	LINZ_parcel_ID	survey_area	calc_area	parcel_geometry	LINZ_parcel_centroid_lon	LINZ_parcel_centroid_lat	LINZ_parcel_vertices_lon	LINZ_parcel_vertices_lat
CL_QPID_output2
2211389	174.690915	-36.764765	2020	POINT (174.69092 -36.76476)	6605986	Lot 109 DP 310598	DP 310598	Fee Simple Title	Primary	None	North Auckland	41583	603.0	603.0	MULTIPOLYGON (((174.69072 -36.76480, 174.69098...	174.690924	-36.764765	[174.69072; 174.690984; 174.691061; 174.691117...	[-36.764801; -36.764606; -36.764662; -36.76473...
2232849	174.690710	-36.764933	2020	POINT (174.69071 -36.76493)	6616860	Lot 68 DP 312607	DP 312607	Fee Simple Title	Primary	None	North Auckland	49611	502.0	502.0	MULTIPOLYGON (((174.69053 -36.76494, 174.69072...	174.690721	-36.764940	[174.69053; 174.69072; 174.690863; 174.690907;...	[-36.764943; -36.764801; -36.764926; -36.76496...